In recent years, there has been a proliferation of consumer digital cameras and camera-equipped mobile devices (e.g., smartphones and tablets). The cost of such devices and digital media storage continue to decrease, while usage continues to increase. Accordingly, there has been an explosion in the amount of digital video data produced and stored. However, much of this data—such as video recorded by surveillance feeds—consists of long-running content which may never be reviewed by a human.
Motion-detection techniques can help automatically identify activities and other elements of interest in video content that might prompt human interest. However, identifying motion-salient regions may impose a tradeoff between accuracy and efficiency. For example, a very fine motion analysis followed by detailed motion segmentation may produce satisfactory results, but the associated overhead generally makes this approach unpractical on computationally constrained devices. On the other hand, raw motion analysis may be performed quickly, but with inaccurate or noisy results.